Detection and Quantification of Coarse Woody Debris in Natural Forest Stands Using Airborne LiDAR

Abstract

AbstractCoarse woody debris (CWD) is a meaningful contributor to forest carbon cycles, wildlife habitat, and biodiversity and can influence wildfire behavior. Using airborne laser scanning (ALS), we map CWD across a range of natural forest stand types in north-central British Columbia, Canada, providing forest managers with spatially detailed information on the presence and volume of ground-level woody biomass. We describe a novel methodology that isolates CWD returns from large diameter logs (>30cm) using a refined grounding algorithm, a mixture of height and pulse-based filters and linear pattern recognition, to transform ALS returns into measurable, vectorized shapes. We then assess the accuracy of CWD detection at the individual log level and predict CWD volume at the plot level. We detected 64% of CWD logs and 79% of CWD volume within our plots. Increased elevation of CWD significantly aided detection (P = 0.04), whereas advanced stages of decay hindered detection (P = 0.04). ALS-predicted CWD volume totals were compared against field-measured CWD and displayed a strong correlation (R = 0.81), allowing us to expand the methodology to map CWD over a larger region. The expanded CWD volume map compared ALS volume predictions between stands and suggests greater volume in stands with older and more heterogeneous stand structure.